segment_mean¶

paddle.geometric. segment_mean ( data, segment_ids, name=None ) [source]

Segment mean Operator.

This operator calculate the mean value of input data which with the same index in segment_ids. It computes a tensor such that $out_i = \frac{1}{n_i} \sum_{j} data[j]$ where sum is over j such that ‘segment_ids[j] == i’ and $n_i$ is the number of all index ‘segment_ids[j] == i’.

Parameters

• data (tensor) – a tensor, available data type float32, float64, int32, int64, float16.

• segment_ids (tensor) – a 1-d tensor, which have the same size with the first dimension of input data. available data type is int32, int64.

• name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

• output (Tensor), the reduced result.

Examples

>>> import paddle
>>> data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32')
>>> segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32')
>>> out = paddle.geometric.segment_mean(data, segment_ids)
>>> print(out.numpy())
[[2. 2. 2.]
 [4. 5. 6.]]